Mühlenbruch Kristin, Ludwig Tonia, Jeppesen Charlotte, Joost Hans-Georg, Rathmann Wolfgang, Meisinger Christine, Peters Annette, Boeing Heiner, Thorand Barbara, Schulze Matthias B
Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany; German Center for Diabetes Research, Germany.
Institute of Epidemiology II, Helmholtz Zentrum München, Neuherberg, Germany; German Center for Diabetes Research, Germany.
Diabetes Res Clin Pract. 2014 Jun;104(3):459-66. doi: 10.1016/j.diabres.2014.03.013. Epub 2014 Mar 28.
Several published diabetes prediction models include information about family history of diabetes. The aim of this study was to extend the previously developed German Diabetes Risk Score (GDRS) with family history of diabetes and to validate the updated GDRS in the Multinational MONItoring of trends and determinants in CArdiovascular Diseases (MONICA)/German Cooperative Health Research in the Region of Augsburg (KORA) study.
We used data from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study for extending the GDRS, including 21,846 participants. Within 5 years of follow-up 492 participants developed diabetes. The definition of family history included information about the father, the mother and/or sibling/s. Model extension was evaluated by discrimination and reclassification. We updated the calculation of the score and absolute risks. External validation was performed in the MONICA/KORA study comprising 11,940 participants with 315 incident cases after 5 years of follow-up.
The basic ROC-AUC of 0.856 (95%-CI: 0.842-0.870) was improved by 0.007 (0.003-0.011) when parent and sibling history was included in the GDRS. The net reclassification improvement was 0.110 (0.072-0.149), respectively. For the updated score we demonstrated good calibration across all tenths of risk. In MONICA/KORA, the ROC-AUC was 0.837 (0.819-0.855); regarding calibration we saw slight overestimation of absolute risks.
Inclusion of the number of diabetes-affected parents and sibling history improved the prediction of type 2 diabetes. Therefore, we updated the GDRS algorithm accordingly. Validation in another German cohort study showed good discrimination and acceptable calibration for the vast majority of individuals.
多项已发表的糖尿病预测模型纳入了糖尿病家族史信息。本研究旨在将先前开发的德国糖尿病风险评分（GDRS）扩展至包含糖尿病家族史，并在心血管疾病多国监测（MONICA）/奥格斯堡地区德国合作健康研究（KORA）中对更新后的GDRS进行验证。
我们使用欧洲癌症与营养前瞻性调查（EPIC）-波茨坦研究的数据来扩展GDRS，该研究包括21846名参与者。在5年随访期内，492名参与者患上糖尿病。家族史的定义包括父亲、母亲和/或兄弟姐妹的信息。通过区分度和重新分类来评估模型扩展情况。我们更新了评分和绝对风险的计算方法。在MONICA/KORA研究中进行外部验证，该研究包括11940名参与者，在5年随访期后有315例新发病例。
当GDRS纳入父母和兄弟姐妹的家族史时，基本受试者工作特征曲线下面积（ROC-AUC）为0.856（95%置信区间：0.842-0.870），提高了0.007（0.003-0.011）。净重新分类改善分别为0.110（0.072-0.149）。对于更新后的评分，我们在所有十分位风险水平上都显示出良好的校准。在MONICA/KORA研究中，ROC-AUC为0.837（0.819-0.855）；在校准方面，我们发现绝对风险略有高估。
纳入受糖尿病影响的父母数量和兄弟姐妹家族史可改善2型糖尿病的预测。因此，我们相应地更新了GDRS算法。在另一项德国队列研究中的验证表明，对于绝大多数个体，该模型具有良好的区分度和可接受的校准。
